Paid Employment of Transition-age Youth with Intellectual Disability and Autism Compared with Other Youth

Employment is one of the most significant markers of independence and success for a person. One’s ability to secure and maintain employment in a paid position can have a significant impact on their overall quality of life, community participation, financial self-sufficiency, and pathway to a long-lasting career. Unfortunately, the paid employment rate for youth and adults with a disability remains markedly lower than their peers without a disability. Our understanding of national employment trends and outcomes for youth with disabilities has been heavily informed by the National Longitudinal Transition Study (NLTS) and NLTS2, with data gathered in 1987–1991 and 2001–2009 respectively. The National Longitudinal Transition Study 2012 (NLTS 2012) dataset offers an updated look at employment of youth in 7th–12th grade with data gathered in 2012–2013. Using the NLTS 2012 data, we examined employment in the past 12 months of youth with intellectual disability (ID) and autism (collectively referred to here as ID/A) compared to other populations of youth with and without disabilities

Multimodal Machine Learning for Automated ICD Coding

This study presents a multimodal machine learning model to predict ICD-10 diagnostic codes. We developed separate machine learning models that can handle data from different modalities, including unstructured text, semi-structured text and structured tabular data. We further employed an ensemble method to integrate all modality-specific models to generate ICD-10 codes. Key evidence was also extracted to make our prediction more convincing and explainable. We used the Medical Information Mart for Intensive Care III (MIMIC -III) dataset to validate our approach. For ICD code prediction, our best-performing model (micro-F1 = 0.7633, micro-AUC = 0.9541) significantly outperforms other baseline models including TF-IDF (micro-F1 = 0.6721, micro-AUC = 0.7879) and Text-CNN model (micro-F1 = 0.6569, micro-AUC = 0.9235). For interpretability, our approach achieves a Jaccard Similarity Coefficient (JSC) of 0.1806 on text data and 0.3105 on tabular data, where well-trained physicians achieve 0.2780 and 0.5002 respectively.Comment: Machine Learning for Healthcare 201

Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study

Background: A major obstacle to effectively treat and control tuberculosis is the absence of an accurate, rapid, and low-cost diagnostic tool. A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms. Methods: We tested a previously published diagnostic algorithm based on four biomarkers as a screening tool for tuberculosis in a Central European patient population using an assessor-blinded cross-sectional study design. In addition, we developed an improved diagnostic classification algorithm based on a study population at a tertiary hospital in Vienna, Austria, by supervised computational statistics. Results: The diagnostic accuracy of the previously published diagnostic algorithm for our patient population consisting of 206 patients was 54% (CI: 47%–61%). An improved model was constructed using inflammation parameters and clinical information. A diagnostic accuracy of 86% (CI: 80%–90%) was demonstrated by 10-fold cross validation. An alternative model relying solely on clinical parameters exhibited a diagnostic accuracy of 85% (CI: 79%–89%). Conclusion: Here we show that a rapid diagnostic algorithm based on clinical parameters is only slightly improved by inclusion of inflammation markers in our cohort. Our results also emphasize the need for validation of new diagnostic algorithms in different settings and patient populations

Antipsychotics and Torsadogenic Risk: Signals Emerging from the US FDA Adverse Event Reporting System Database

Background: Drug-induced torsades de pointes (TdP) and related clinical entities represent a current regulatory and clinical burden. Objective: As part of the FP7 ARITMO (Arrhythmogenic Potential of Drugs) project, we explored the publicly available US FDA Adverse Event Reporting System (FAERS) database to detect signals of torsadogenicity for antipsychotics (APs). Methods: Four groups of events in decreasing order of drug-attributable risk were identified: (1) TdP, (2) QT-interval abnormalities, (3) ventricular fibrillation/tachycardia, and (4) sudden cardiac death. The reporting odds ratio (ROR) with 95 % confidence interval (CI) was calculated through a cumulative analysis from group 1 to 4. For groups 1+2, ROR was adjusted for age, gender, and concomitant drugs (e.g., antiarrhythmics) and stratified for AZCERT drugs, lists I and II (http://www.azcert.org, as of June 2011). A potential signal of torsadogenicity was defined if a drug met all the following criteria: (a) four or more cases in group 1+2; (b) significant ROR in group 1+2 that persists through the cumulative approach; (c) significant adjusted ROR for group 1+2 in the stratum without AZCERT drugs; (d) not included in AZCERT lists (as of June 2011). Results: Over the 7-year period, 37 APs were reported in 4,794 cases of arrhythmia: 140 (group 1), 883 (group 2), 1,651 (group 3), and 2,120 (group 4). Based on our criteria, the following potential signals of torsadogenicity were found: amisulpride (25 cases; adjusted ROR in the stratum without AZCERT drugs = 43.94, 95 % CI 22.82-84.60), cyamemazine (11; 15.48, 6.87-34.91), and olanzapine (189; 7.74, 6.45-9.30). Conclusions: This pharmacovigilance analysis on the FAERS found 3 potential signals of torsadogenicity for drugs previously unknown for this risk

The "Ram Effect": A "Non-Classical" Mechanism for Inducing LH Surges in Sheep

During spring sheep do not normally ovulate but exposure to a ram can induce ovulation. In some ewes an LH surge is induced immediately after exposure to a ram thus raising questions about the control of this precocious LH surge. Our first aim was to determine the plasma concentrations of oestradiol (E2) E2 in anoestrous ewes before and after the "ram effect" in ewes that had a "precocious" LH surge (starting within 6 hours), a "normal" surge (between 6 and 28h) and "late» surge (not detected by 56h). In another experiment we tested if a small increase in circulating E2 could induce an LH surge in anoestrus ewes. The concentration of E2 significantly was not different at the time of ram introduction among ewes with the three types of LH surge. "Precocious" LH surges were not preceded by a large increase in E2 unlike "normal" surges and small elevations of circulating E2 alone were unable to induce LH surges. These results show that the "precocious" LH surge was not the result of E2 positive feedback. Our second aim was to test if noradrenaline (NA) is involved in the LH response to the "ram effect". Using double labelling for Fos and tyrosine hydroxylase (TH) we showed that exposure of anoestrous ewes to a ram induced a higher density of cells positive for both in the A1 nucleus and the Locus Coeruleus complex compared to unstimulated controls. Finally, the administration by retrodialysis into the preoptic area, of NA increased the proportion of ewes with an LH response to ram odor whereas treatment with the α1 antagonist Prazosin decreased the LH pulse frequency and amplitude induced by a sexually active ram. Collectively these results suggest that in anoestrous ewes NA is involved in ram-induced LH secretion as observed in other induced ovulators

Validation of diagnostic accuracy using digital slides in routine histopathology

Background: Robust hardware and software tools have been developed in digital microscopy during the past years for pathologists. Reports have been advocated the reliability of digital slides in routine diagnostics. We have designed a retrospective, comparative study to evaluate the scanning properties and digital slide based diagnostic accuracy. Methods: 8 pathologists reevaluated 306 randomly selected cases from our archives. The slides were scanned with a 20 × Plan-Apochromat objective, using a 3-chip Hitachi camera, resulting 0.465 μm/pixel resolution. Slide management was supported with dedicated Data Base and Viewer software tools. Pathologists used their office PCs for evaluation and reached the digital slides via intranet connection. The diagnostic coherency and uncertainty related to digital slides and scanning quality were analyzed. Results: Good to excellent image quality of slides was recorded in 96%. In half of the critical 61 digital slides, poor image quality was related to section folds or floatings. In 88.2 % of the studied cases the digital diagnoses were in full agreement with the consensus. Out of the overall 36 incoherent cases, 7 (2.3%) were graded relevant without any recorded uncertainty by the pathologist. Excluding the non-field specific cases from each pathologist’s record this ratio was 1.76 % of all cases. Conclusions: Our results revealed that: 1) digital slide based histopathological diagnoses can be highly coherent with those using optical microscopy; 2) the competency of pathologists is a factor more important than the quality of digital slide; 3) poor digital slide quality do not endanger patient safety as these errors are recognizable by the pathologist and further actions for correction could be taken. Virtual slides: The virtual slide(s) for this article can be found here

Surgery versus Watchful Waiting in Patients with Craniofacial Fibrous Dysplasia – a Meta-Analysis

Fibrous dysplasia (FD) is a benign bone tumor which most commonly involves the craniofacial skeleton. The most devastating consequence of craniofacial FD (CFD) is loss of vision due to optic nerve compression (ONC). Radiological evidence of ONC is common, however the management of this condition is not well established. Our objective was to compare the long-term outcome of patients with optic nerve compression (ONC) due to craniofacial fibrous dysplasia (CFD) who either underwent surgery or were managed expectantly.We performed a meta-analysis of 27 studies along with analysis of the records of a cohort of patients enrolled in National Institutes of Health (NIH) protocol 98-D-0145, entitled Screening and Natural History of Fibrous Dysplasia, with a diagnosis of CFD. The study group consisted of 241 patients; 122 were enrolled in the NIH study and 119 were extracted from cases published in the literature. The median follow-up period was 54 months (range, 6-228 months). A total of 368 optic nerves were investigated. All clinically impaired optic nerves (n = 86, 23.3%) underwent therapeutic decompression. Of the 282 clinically intact nerves, 41 (15%) were surgically decompressed and 241 (85%) were followed expectantly. Improvement in visual function was reported in fifty-eight (67.4%) of the clinically impaired nerves after surgery. In the intact nerves group, long-term stable vision was achieved in 31/45 (75.6%) of the operated nerves, compared to 229/241 (95.1%) of the non-operated ones (p = 0.0003). Surgery in asymptomatic patients was associated with visual deterioration (RR 4.89; 95% CI 2.26-10.59).Most patients with CFD will remain asymptomatic during long-term follow-up. Expectant management is recommended in asymptomatic patients even in the presence of radiological evidence of ONC

In epithelial cancers, aberrant COL17A1 promoter methylation predicts its misexpression and increased invasion

Background: Metastasis is a leading cause of death among cancer patients. In the tumor microenvironment, altered levels of extracellular matrix proteins, such as collagens, can facilitate the first steps of cancer cell metastasis, including invasion into surrounding tissue and intravasation into the blood stream. However, the degree of misexpression of collagen genes in tumors remains understudied, even though this knowledge could greatly facilitate the development of cancer treatment options aimed at preventing metastasis. Methods: We systematically evaluate the expression of all 44 collagen genes in breast cancer and assess whether their misexpression provides clinical prognostic significance. We use immunohistochemistry on 150 ductal breast cancers and 361 cervical cancers and study DNA methylation in various epithelial cancers. Results: In breast cancer, various tests show that COL4A1 and COL4A2 overexpression and COL17A1 (BP180, BPAG2) underexpression provide independent prognostic strength (HR = 1.25, 95% CI = 1.17–1.34, p = 3.03 × 10; HR = 1.18, 95% CI = 1.11–1.25, p = 8.11 × 10; HR = 0.86, 95% CI = 0.81–0.92, p = 4.57 × 10; respectively). Immunohistochemistry on ductal breast cancers confirmed that the COL17A1 protein product, collagen XVII, is underexpressed. This strongly correlates with advanced stage, increased invasion, and postmenopausal status. In contrast, immunohistochemistry on cervical tumors showed that collagen XVII is overexpressed in cervical cancer and this is associated with increased local dissemination. Interestingly, consistent with the opposed direction of misexpression in these cancers, the COL17A1 promoter is hypermethylated in breast cancer and hypomethylated in cervical cancer. We also find that the COL17A1 promoter is hypomethylated in head and neck squamous cell carcinoma, lung squamous cell carcinoma, and lung adenocarcinoma, in all of which collagen XVII overexpression has previously been shown. Conclusions: Paradoxically, collagen XVII is underexpressed in breast cancer and overexpressed in cervical and other epithelial cancers. However, the COL17A1 promoter methylation status accurately predicts both the direction of misexpression and the increased invasive nature for five out of five epithelial cancers. This implies that aberrant epigenetic control is a key driver of COL17A1 gene misexpression and tumor cell invasion. These findings have significant clinical implications, suggesting that the COL17A1 promoter methylation status can be used to predict patient outcome. Moreover, epigenetic targeting of COL17A1 could represent a novel strategy to prevent metastasis in patients

Fatigue In Teenagers on the interNET - The FITNET Trial. A randomized clinical trial of web-based cognitive behavioural therapy for adolescents with chronic fatigue syndrome: study protocol. [ISRCTN59878666]

Contains fulltext : 97913.pdf (publisher's version ) (Open Access)BACKGROUND: Chronic Fatigue Syndrome (CFS) is increasingly recognized as a cause of disability and inactivity in adolescents in the Netherlands. CFS is characterized by unexplained fatigue lasting more than 6 months. Cognitive Behavioural Therapy (CBT) has proven to be effective. However, CBT availability for adolescents with CFS is limited and requires special therapeutic skills not always readily available. An alternative to the face-to-face CBT is FITNET, a web-based therapeutic program designed specifically for adolescents diagnosed with CFS, and their parents. This new CBT approach appeals to the modern youth, who grow up with internet as their main source of information. A web-based program offers the opportunity to lower thresholds for the acceptance and realization of healthcare. This treatment can be activated at any chosen time. The communication between patient and therapist can elapse asynchronously. If effective, this web-based program would greatly increase the therapeutic accessibility. METHODS/DESIGN: A randomized clinical trial is currently conducted. One-hundred-forty adolescents aged 12-18 years diagnosed with CFS will be recruited and randomized to one of two groups: FITNET or usual care. After 6 months, the usual care group will have access to the FITNET program. Outcomes will be assessed at baseline, post intervention, and at 6 months follow-up. Primary outcome measures are school presence, fatigue severity, and physical functioning. DISCUSSION: The FITNET study is the first randomized clinical trial which evaluates the effect of web-based CBT versus usual care in adolescents with CFS. The intervention is based on a theoretical existing model of CBT for patients with CFS. The results of this study will provide information about the possibility and efficacy of web-based CBT for adolescents with CFS and will reveal predictors of efficacy. TRIAL REGISTRATION: ISRCTN: ISRCTN59878666 and ClinicalTrials.gov: NCT00893438